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--- a +++ b/DEMO/Transformer+CNN_BindingDB.ipynb @@ -0,0 +1,330 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "os.chdir('../')\n", + "\n", + "import DeepPurpose.DTI as models\n", + "from DeepPurpose.utils import *\n", + "from DeepPurpose.dataset import *" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "X_drug, X_target, y = process_BindingDB('../data/BindingDB_All.tsv',\n", + " y = 'Kd', \n", + " binary = False, \n", + " convert_to_log = True)\n", + "\n", + "drug_encoding = 'Transformer'\n", + "target_encoding = 'CNN'\n", + "train, val, test = data_process(X_drug, X_target, y, \n", + " drug_encoding, target_encoding, \n", + " split_method='random',frac=[0.7,0.1,0.2])\n", + "\n", + "config = generate_config(drug_encoding = drug_encoding, \n", + " target_encoding = target_encoding, \n", + " cls_hidden_dims = [1024,1024,512], \n", + " train_epoch = 100, \n", + " LR = 0.001, \n", + " batch_size = 128,\n", + " cnn_target_filters = [32,64,96],\n", + " cnn_target_kernels = [4,8,12]\n", + " )" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Let's use 1 GPU/s!\n", + "--- Data Preparation ---\n", + "--- Go for Training ---\n", + "Training at Epoch 1 iteration 0 with loss 29.634226\n", + "Validation at Epoch 1 , MSE: 0.725780701567487 , Pearson Correlation: 0.40398057707518564 with p-value: 2.1550998167531695e-118 , Concordance Index: 0.7271688926134408\n", + "Training at Epoch 2 iteration 0 with loss 0.603022\n", + "Validation at Epoch 2 , MSE: 0.5726512454403675 , Pearson Correlation: 0.4879649393084924 with p-value: 1.1928492107245293e-179 , Concordance Index: 0.7650372191652788\n", + "Training at Epoch 3 iteration 0 with loss 0.72227985\n", + "Validation at Epoch 3 , MSE: 0.5525040086756707 , Pearson Correlation: 0.5356641450331265 with p-value: 6.8038841647049305e-223 , Concordance Index: 0.7804433797848193\n", + "Training at Epoch 4 iteration 0 with loss 0.6410252\n", + "Validation at Epoch 4 , MSE: 0.5703041501774694 , Pearson Correlation: 0.5541856884617206 with p-value: 1.2183007747425456e-241 , Concordance Index: 0.7877413931229313\n", + "Training at Epoch 5 iteration 0 with loss 0.57430494\n", + "Validation at Epoch 5 , MSE: 0.5264440393985904 , Pearson Correlation: 0.5592105171132391 with p-value: 6.214448893917246e-247 , Concordance Index: 0.7847017986774327\n", + "Training at Epoch 6 iteration 0 with loss 0.46163726\n", + "Validation at Epoch 6 , MSE: 0.5239591018950978 , Pearson Correlation: 0.5796159020612044 with p-value: 2.1912349762338032e-269 , Concordance Index: 0.7858452975776358\n", + "Training at Epoch 7 iteration 0 with loss 0.4550215\n", + "Validation at Epoch 7 , MSE: 0.603541948413404 , Pearson Correlation: 0.5977550269084122 with p-value: 1.0080912609304493e-290 , Concordance Index: 0.7991921939015735\n", + "Training at Epoch 8 iteration 0 with loss 0.8301095\n", + "Validation at Epoch 8 , MSE: 0.47116111386615533 , Pearson Correlation: 0.620885790442645 with p-value: 5.3774e-320 , Concordance Index: 0.8144086132017794\n", + "Training at Epoch 9 iteration 0 with loss 0.53142715\n", + "Validation at Epoch 9 , MSE: 0.4731906554424334 , Pearson Correlation: 0.6248141951232127 with p-value: 0.0 , Concordance Index: 0.8160135085278182\n", + "Training at Epoch 10 iteration 0 with loss 0.38353115\n", + "Validation at Epoch 10 , MSE: 0.46101175617190526 , Pearson Correlation: 0.6225610887191967 with p-value: 3.26e-322 , Concordance Index: 0.8121991370283699\n", + "Training at Epoch 11 iteration 0 with loss 0.46544605\n", + "Validation at Epoch 11 , MSE: 0.46800647421793545 , Pearson Correlation: 0.6253235457508556 with p-value: 0.0 , Concordance Index: 0.8152806766034898\n", + "Training at Epoch 12 iteration 0 with loss 0.38787222\n", + "Validation at Epoch 12 , MSE: 0.49059348332642927 , Pearson Correlation: 0.6305917266000525 with p-value: 0.0 , Concordance Index: 0.8156961749555514\n", + "Training at Epoch 13 iteration 0 with loss 0.39777344\n", + "Validation at Epoch 13 , MSE: 0.4597835762560362 , Pearson Correlation: 0.6352527111758693 with p-value: 0.0 , Concordance Index: 0.8220503130731769\n", + "Training at Epoch 14 iteration 0 with loss 0.48289645\n", + "Validation at Epoch 14 , MSE: 0.5861588663676301 , Pearson Correlation: 0.6272275470144072 with p-value: 0.0 , Concordance Index: 0.8210223279854391\n", + "Training at Epoch 15 iteration 0 with loss 0.42192978\n", + "Validation at Epoch 15 , MSE: 0.4734210217624147 , Pearson Correlation: 0.6358734159533941 with p-value: 0.0 , Concordance Index: 0.8235792240282784\n", + "Training at Epoch 16 iteration 0 with loss 0.54570305\n", + "Validation at Epoch 16 , MSE: 0.4483271668059146 , Pearson Correlation: 0.6346897365941144 with p-value: 0.0 , Concordance Index: 0.821825434472484\n", + "Training at Epoch 17 iteration 0 with loss 0.39541918\n", + "Validation at Epoch 17 , MSE: 0.4597622381052897 , Pearson Correlation: 0.640353421862969 with p-value: 0.0 , Concordance Index: 0.8175865606926261\n", + "Training at Epoch 18 iteration 0 with loss 0.48001066\n", + "Validation at Epoch 18 , MSE: 0.46439951930078865 , Pearson Correlation: 0.6293227898188998 with p-value: 0.0 , Concordance Index: 0.8188172439721993\n", + "Training at Epoch 19 iteration 0 with loss 0.40129694\n", + "Validation at Epoch 19 , MSE: 0.5442128498468414 , Pearson Correlation: 0.6418123629203649 with p-value: 0.0 , Concordance Index: 0.8187891341471127\n", + "Training at Epoch 20 iteration 0 with loss 0.44739527\n", + "Validation at Epoch 20 , MSE: 0.46979231787575587 , Pearson Correlation: 0.637766837211485 with p-value: 0.0 , Concordance Index: 0.8225892311260093\n", + "Training at Epoch 21 iteration 0 with loss 0.39083403\n", + "Validation at Epoch 21 , MSE: 0.45506637193870014 , Pearson Correlation: 0.6378444966625737 with p-value: 0.0 , Concordance Index: 0.8162544185131309\n", + "Training at Epoch 22 iteration 0 with loss 0.3153687\n", + "Validation at Epoch 22 , MSE: 0.43271781241925056 , Pearson Correlation: 0.6537836051217082 with p-value: 0.0 , Concordance Index: 0.8230220785107415\n", + "Training at Epoch 23 iteration 0 with loss 0.47659552\n", + "Validation at Epoch 23 , MSE: 0.4399627166532394 , Pearson Correlation: 0.6521851528257023 with p-value: 0.0 , Concordance Index: 0.8268768578837519\n", + "Training at Epoch 24 iteration 0 with loss 0.3663129\n", + "Validation at Epoch 24 , MSE: 0.4258856862760016 , Pearson Correlation: 0.6610090449894297 with p-value: 0.0 , Concordance Index: 0.8240911302960667\n", + "Training at Epoch 25 iteration 0 with loss 0.43668756\n", + "Validation at Epoch 25 , MSE: 0.4397800038391447 , Pearson Correlation: 0.6768974035707589 with p-value: 0.0 , Concordance Index: 0.8259165120626287\n", + "Training at Epoch 26 iteration 0 with loss 0.34239262\n", + "Validation at Epoch 26 , MSE: 0.4192124405888546 , Pearson Correlation: 0.6744930768817405 with p-value: 0.0 , Concordance Index: 0.8266732812598824\n", + "Training at Epoch 27 iteration 0 with loss 0.4119158\n", + "Validation at Epoch 27 , MSE: 0.47391782450429887 , Pearson Correlation: 0.6825673019129879 with p-value: 0.0 , Concordance Index: 0.8307496451134583\n", + "Training at Epoch 28 iteration 0 with loss 0.39092425\n", + "Validation at Epoch 28 , MSE: 0.4031011979798852 , Pearson Correlation: 0.6889372903149931 with p-value: 0.0 , Concordance Index: 0.8362962845838692\n", + "Training at Epoch 29 iteration 0 with loss 0.47543424\n", + "Validation at Epoch 29 , MSE: 0.5850640718990475 , Pearson Correlation: 0.6976275074647019 with p-value: 0.0 , Concordance Index: 0.8363037512561579\n", + "Training at Epoch 30 iteration 0 with loss 0.46826386\n", + "Validation at Epoch 30 , MSE: 0.4427272234655412 , Pearson Correlation: 0.7156511424054299 with p-value: 0.0 , Concordance Index: 0.845776103486321\n", + "Training at Epoch 31 iteration 0 with loss 0.39572835\n", + "Validation at Epoch 31 , MSE: 0.4159521700411212 , Pearson Correlation: 0.721940879091033 with p-value: 0.0 , Concordance Index: 0.848868403853857\n", + "Training at Epoch 32 iteration 0 with loss 0.34805343\n", + "Validation at Epoch 32 , MSE: 0.47982745623956036 , Pearson Correlation: 0.7197250691390631 with p-value: 0.0 , Concordance Index: 0.8385477058869001\n", + "Training at Epoch 33 iteration 0 with loss 0.36586666\n", + "Validation at Epoch 33 , MSE: 0.3795555466341415 , Pearson Correlation: 0.7290503381217495 with p-value: 0.0 , Concordance Index: 0.843455066444599\n", + "Training at Epoch 34 iteration 0 with loss 0.26864153\n", + "Validation at Epoch 34 , MSE: 0.412939738777511 , Pearson Correlation: 0.7283244630639841 with p-value: 0.0 , Concordance Index: 0.8455540797897385\n", + "Training at Epoch 35 iteration 0 with loss 0.36693335\n", + "Validation at Epoch 35 , MSE: 0.3665921494083899 , Pearson Correlation: 0.7407322026875887 with p-value: 0.0 , Concordance Index: 0.8459401506686625\n", + "Training at Epoch 36 iteration 0 with loss 0.36277795\n", + "Validation at Epoch 36 , MSE: 0.33976943758227934 , Pearson Correlation: 0.7405918998493471 with p-value: 0.0 , Concordance Index: 0.8449833185756752\n", + "Training at Epoch 37 iteration 0 with loss 0.24880204\n", + "Validation at Epoch 37 , MSE: 0.36297318059187794 , Pearson Correlation: 0.7359023640901088 with p-value: 0.0 , Concordance Index: 0.8513539272939374\n", + "Training at Epoch 38 iteration 0 with loss 0.24418767\n", + "Validation at Epoch 38 , MSE: 0.3426421185842073 , Pearson Correlation: 0.7467750468676866 with p-value: 0.0 , Concordance Index: 0.8473825360684193\n", + "Training at Epoch 39 iteration 0 with loss 0.23802906\n", + "Validation at Epoch 39 , MSE: 0.3255335815045136 , Pearson Correlation: 0.7543405491409306 with p-value: 0.0 , Concordance Index: 0.8466336727594712\n", + "Training at Epoch 40 iteration 0 with loss 0.24160706\n", + "Validation at Epoch 40 , MSE: 0.3680416253290795 , Pearson Correlation: 0.742739550846127 with p-value: 0.0 , Concordance Index: 0.8419628300269152\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Training at Epoch 41 iteration 0 with loss 0.33248448\n", + "Validation at Epoch 41 , MSE: 0.33023237135946826 , Pearson Correlation: 0.7516039622218981 with p-value: 0.0 , Concordance Index: 0.8528141009423819\n", + "Training at Epoch 42 iteration 0 with loss 0.20897366\n", + "Validation at Epoch 42 , MSE: 0.3329422987347984 , Pearson Correlation: 0.7564631221299889 with p-value: 0.0 , Concordance Index: 0.8556202520748565\n", + "Training at Epoch 43 iteration 0 with loss 0.24069251\n", + "Validation at Epoch 43 , MSE: 0.4077519352355681 , Pearson Correlation: 0.7507050947749823 with p-value: 0.0 , Concordance Index: 0.8482908347915306\n", + "Training at Epoch 44 iteration 0 with loss 0.24760874\n", + "Validation at Epoch 44 , MSE: 0.3292789245976155 , Pearson Correlation: 0.7528507687958774 with p-value: 0.0 , Concordance Index: 0.8400832050822564\n", + "Training at Epoch 45 iteration 0 with loss 0.20775744\n", + "Validation at Epoch 45 , MSE: 0.31573009775373134 , Pearson Correlation: 0.7624827822071432 with p-value: 0.0 , Concordance Index: 0.8459401506686625\n", + "Training at Epoch 46 iteration 0 with loss 0.20031127\n", + "Validation at Epoch 46 , MSE: 0.33393605006112004 , Pearson Correlation: 0.7541164997206213 with p-value: 0.0 , Concordance Index: 0.8552783224056388\n", + "Training at Epoch 47 iteration 0 with loss 0.14390057\n", + "Validation at Epoch 47 , MSE: 0.3063054240751083 , Pearson Correlation: 0.774190013606482 with p-value: 0.0 , Concordance Index: 0.8582307324717672\n", + "Training at Epoch 48 iteration 0 with loss 0.17719845\n", + "Validation at Epoch 48 , MSE: 0.3111927910132231 , Pearson Correlation: 0.7697922966528918 with p-value: 0.0 , Concordance Index: 0.8572269042649632\n", + "Training at Epoch 49 iteration 0 with loss 0.23493817\n", + "Validation at Epoch 49 , MSE: 0.38880321812484453 , Pearson Correlation: 0.7686184811645655 with p-value: 0.0 , Concordance Index: 0.8534186817897526\n", + "Training at Epoch 50 iteration 0 with loss 0.26537552\n", + "Validation at Epoch 50 , MSE: 0.3117944822270837 , Pearson Correlation: 0.7697944636844831 with p-value: 0.0 , Concordance Index: 0.8575815711986732\n", + "Training at Epoch 51 iteration 0 with loss 0.2059507\n", + "Validation at Epoch 51 , MSE: 0.35994106974982654 , Pearson Correlation: 0.7724793895602798 with p-value: 0.0 , Concordance Index: 0.8604639263100935\n", + "Training at Epoch 52 iteration 0 with loss 0.29771197\n", + "Validation at Epoch 52 , MSE: 0.30243781151683097 , Pearson Correlation: 0.774970433073671 with p-value: 0.0 , Concordance Index: 0.8596504982466496\n", + "Training at Epoch 53 iteration 0 with loss 0.13921075\n", + "Validation at Epoch 53 , MSE: 0.3166499760629699 , Pearson Correlation: 0.7697556007106207 with p-value: 0.0 , Concordance Index: 0.8538225409173641\n", + "Training at Epoch 54 iteration 0 with loss 0.2019538\n", + "Validation at Epoch 54 , MSE: 0.31847235681748987 , Pearson Correlation: 0.7654841044450228 with p-value: 0.0 , Concordance Index: 0.8566304489139066\n", + "Training at Epoch 55 iteration 0 with loss 0.17592895\n", + "Validation at Epoch 55 , MSE: 0.32140615317544025 , Pearson Correlation: 0.7796043192450737 with p-value: 0.0 , Concordance Index: 0.856714558781158\n", + "Training at Epoch 56 iteration 0 with loss 0.1588264\n", + "Validation at Epoch 56 , MSE: 0.2933640105662261 , Pearson Correlation: 0.7816763328240687 with p-value: 0.0 , Concordance Index: 0.8673932178019522\n", + "Training at Epoch 57 iteration 0 with loss 0.18687354\n", + "Validation at Epoch 57 , MSE: 0.3086026125372463 , Pearson Correlation: 0.7743889549515655 with p-value: 0.0 , Concordance Index: 0.8571318139972874\n", + "Training at Epoch 58 iteration 0 with loss 0.19043419\n", + "Validation at Epoch 58 , MSE: 0.3167679398534858 , Pearson Correlation: 0.7785929443516493 with p-value: 0.0 , Concordance Index: 0.8625517396468001\n", + "Training at Epoch 59 iteration 0 with loss 0.18739408\n", + "Validation at Epoch 59 , MSE: 0.3766276346080875 , Pearson Correlation: 0.7619611139553615 with p-value: 0.0 , Concordance Index: 0.8616711115327584\n", + "Training at Epoch 60 iteration 0 with loss 0.22643688\n", + "Validation at Epoch 60 , MSE: 0.2929906934487656 , Pearson Correlation: 0.7820891683717808 with p-value: 0.0 , Concordance Index: 0.8673539079684327\n", + "Training at Epoch 61 iteration 0 with loss 0.16580065\n", + "Validation at Epoch 61 , MSE: 0.4560569024952441 , Pearson Correlation: 0.7672895648856787 with p-value: 0.0 , Concordance Index: 0.8589492898755438\n", + "Training at Epoch 62 iteration 0 with loss 0.37498075\n", + "Validation at Epoch 62 , MSE: 0.3485699448628535 , Pearson Correlation: 0.7723602560927123 with p-value: 0.0 , Concordance Index: 0.851666209882009\n", + "Training at Epoch 63 iteration 0 with loss 0.14209083\n", + "Validation at Epoch 63 , MSE: 0.31027944286285397 , Pearson Correlation: 0.7856141845805611 with p-value: 0.0 , Concordance Index: 0.8625548141589189\n", + "Training at Epoch 64 iteration 0 with loss 0.13787936\n", + "Validation at Epoch 64 , MSE: 0.2978461283957146 , Pearson Correlation: 0.7863738487357339 with p-value: 0.0 , Concordance Index: 0.8635557874616125\n", + "Training at Epoch 65 iteration 0 with loss 0.16634636\n", + "Validation at Epoch 65 , MSE: 0.28281064973311476 , Pearson Correlation: 0.7914869465988887 with p-value: 0.0 , Concordance Index: 0.8665721034582112\n", + "Training at Epoch 66 iteration 0 with loss 0.16248938\n", + "Validation at Epoch 66 , MSE: 0.3356534599631882 , Pearson Correlation: 0.7775138080960353 with p-value: 0.0 , Concordance Index: 0.8527831362131849\n", + "Training at Epoch 67 iteration 0 with loss 0.17652586\n", + "Validation at Epoch 67 , MSE: 0.3067052467119645 , Pearson Correlation: 0.7867424585931191 with p-value: 0.0 , Concordance Index: 0.8649564473397564\n", + "Training at Epoch 68 iteration 0 with loss 0.14171846\n", + "Validation at Epoch 68 , MSE: 0.31755287723766024 , Pearson Correlation: 0.782436550684411 with p-value: 0.0 , Concordance Index: 0.866221828684671\n", + "Training at Epoch 69 iteration 0 with loss 0.14237842\n", + "Validation at Epoch 69 , MSE: 0.34041388161182545 , Pearson Correlation: 0.7899690388915522 with p-value: 0.0 , Concordance Index: 0.8655480713146263\n", + "Training at Epoch 70 iteration 0 with loss 0.2093993\n", + "Validation at Epoch 70 , MSE: 0.28555122295025404 , Pearson Correlation: 0.7976450577205181 with p-value: 0.0 , Concordance Index: 0.8718806878474199\n", + "Training at Epoch 71 iteration 0 with loss 0.13721466\n", + "Validation at Epoch 71 , MSE: 0.2861693923533604 , Pearson Correlation: 0.7880974203176389 with p-value: 0.0 , Concordance Index: 0.8708390870631557\n", + "Training at Epoch 72 iteration 0 with loss 0.080976\n", + "Validation at Epoch 72 , MSE: 0.2939428775194183 , Pearson Correlation: 0.7843787271576592 with p-value: 0.0 , Concordance Index: 0.8657731695233276\n", + "Training at Epoch 73 iteration 0 with loss 0.15536982\n", + "Validation at Epoch 73 , MSE: 0.29759863823311794 , Pearson Correlation: 0.7787653372195861 with p-value: 0.0 , Concordance Index: 0.8576588732176614\n", + "Training at Epoch 74 iteration 0 with loss 0.10382487\n", + "Validation at Epoch 74 , MSE: 0.31064877717782885 , Pearson Correlation: 0.7745366882267296 with p-value: 0.0 , Concordance Index: 0.8602845065671579\n", + "Training at Epoch 75 iteration 0 with loss 0.10860255\n", + "Validation at Epoch 75 , MSE: 0.29593183945611423 , Pearson Correlation: 0.7865838770327085 with p-value: 0.0 , Concordance Index: 0.8653526201870709\n", + "Training at Epoch 76 iteration 0 with loss 0.09611059\n", + "Validation at Epoch 76 , MSE: 0.29878144466376433 , Pearson Correlation: 0.7851372671838887 with p-value: 0.0 , Concordance Index: 0.8606042558275181\n", + "Training at Epoch 77 iteration 0 with loss 0.13595721\n", + "Validation at Epoch 77 , MSE: 0.3402778819122518 , Pearson Correlation: 0.7823734120003081 with p-value: 0.0 , Concordance Index: 0.8628078025846985\n", + "Training at Epoch 78 iteration 0 with loss 0.21282764\n", + "Validation at Epoch 78 , MSE: 0.28612222489712985 , Pearson Correlation: 0.7928125245940223 with p-value: 0.0 , Concordance Index: 0.8663294366088307\n", + "Training at Epoch 79 iteration 0 with loss 0.09100406\n", + "Validation at Epoch 79 , MSE: 0.29902305999838713 , Pearson Correlation: 0.7925053616587834 with p-value: 0.0 , Concordance Index: 0.874747231182229\n", + "Training at Epoch 80 iteration 0 with loss 0.13347423\n", + "Validation at Epoch 80 , MSE: 0.31253688722776996 , Pearson Correlation: 0.784692023213976 with p-value: 0.0 , Concordance Index: 0.8569089118686709\n", + "Training at Epoch 81 iteration 0 with loss 0.12549114\n", + "Validation at Epoch 81 , MSE: 0.3010081206304513 , Pearson Correlation: 0.7825805965200501 with p-value: 0.0 , Concordance Index: 0.8637305954363699\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Training at Epoch 82 iteration 0 with loss 0.1079582\n", + "Validation at Epoch 82 , MSE: 0.29168211834795316 , Pearson Correlation: 0.7942657867509696 with p-value: 0.0 , Concordance Index: 0.869972294253649\n", + "Training at Epoch 83 iteration 0 with loss 0.07591695\n", + "Validation at Epoch 83 , MSE: 0.29756025245344164 , Pearson Correlation: 0.7943579943692158 with p-value: 0.0 , Concordance Index: 0.8691799485590201\n", + "Training at Epoch 84 iteration 0 with loss 0.07741684\n", + "Validation at Epoch 84 , MSE: 0.29357583706887136 , Pearson Correlation: 0.8010128081235468 with p-value: 0.0 , Concordance Index: 0.8742335680503728\n", + "Training at Epoch 85 iteration 0 with loss 0.090614535\n", + "Validation at Epoch 85 , MSE: 0.2859333284412329 , Pearson Correlation: 0.7988325976461027 with p-value: 0.0 , Concordance Index: 0.8749890195995755\n", + "Training at Epoch 86 iteration 0 with loss 0.11960477\n", + "Validation at Epoch 86 , MSE: 0.29872324837589437 , Pearson Correlation: 0.7852945263006591 with p-value: 0.0 , Concordance Index: 0.8693868193030169\n", + "Training at Epoch 87 iteration 0 with loss 0.09527132\n", + "Validation at Epoch 87 , MSE: 0.29218811961414093 , Pearson Correlation: 0.7907322467554618 with p-value: 0.0 , Concordance Index: 0.8661140011525028\n", + "Training at Epoch 88 iteration 0 with loss 0.10724583\n", + "Validation at Epoch 88 , MSE: 0.28132808310724317 , Pearson Correlation: 0.7965797527606073 with p-value: 0.0 , Concordance Index: 0.8731003907265688\n", + "Training at Epoch 89 iteration 0 with loss 0.11214432\n", + "Validation at Epoch 89 , MSE: 0.2812944953479944 , Pearson Correlation: 0.7984507127024164 with p-value: 0.0 , Concordance Index: 0.8746686115151898\n", + "Training at Epoch 90 iteration 0 with loss 0.110264264\n", + "Validation at Epoch 90 , MSE: 0.2943626711714906 , Pearson Correlation: 0.7958484242200626 with p-value: 0.0 , Concordance Index: 0.8698635882894469\n", + "Training at Epoch 91 iteration 0 with loss 0.11829962\n", + "Validation at Epoch 91 , MSE: 0.28645835748872467 , Pearson Correlation: 0.7907913600411716 with p-value: 0.0 , Concordance Index: 0.8659257970892276\n", + "Training at Epoch 92 iteration 0 with loss 0.12059486\n", + "Validation at Epoch 92 , MSE: 0.2956916409092075 , Pearson Correlation: 0.7918484698618803 with p-value: 0.0 , Concordance Index: 0.8699617530692415\n", + "Training at Epoch 93 iteration 0 with loss 0.0967102\n", + "Validation at Epoch 93 , MSE: 0.3069302997519912 , Pearson Correlation: 0.7874464559359134 with p-value: 0.0 , Concordance Index: 0.8596871727840674\n", + "Training at Epoch 94 iteration 0 with loss 0.13414422\n", + "Validation at Epoch 94 , MSE: 0.28288662992067215 , Pearson Correlation: 0.7947025411715298 with p-value: 0.0 , Concordance Index: 0.8659552245623652\n", + "Training at Epoch 95 iteration 0 with loss 0.10370281\n", + "Validation at Epoch 95 , MSE: 0.28695570933638226 , Pearson Correlation: 0.7927755234564616 with p-value: 0.0 , Concordance Index: 0.8643083841067049\n", + "Training at Epoch 96 iteration 0 with loss 0.13430275\n", + "Validation at Epoch 96 , MSE: 0.3258646538582383 , Pearson Correlation: 0.7833035914012931 with p-value: 0.0 , Concordance Index: 0.8716263817735894\n", + "Training at Epoch 97 iteration 0 with loss 0.14196697\n", + "Validation at Epoch 97 , MSE: 0.2896430110049083 , Pearson Correlation: 0.7894914155305123 with p-value: 0.0 , Concordance Index: 0.864822925670595\n", + "Training at Epoch 98 iteration 0 with loss 0.0765197\n", + "Validation at Epoch 98 , MSE: 0.2824313373215666 , Pearson Correlation: 0.7947989487940375 with p-value: 0.0 , Concordance Index: 0.8668753821179348\n", + "Training at Epoch 99 iteration 0 with loss 0.0673421\n", + "Validation at Epoch 99 , MSE: 0.3075603177427848 , Pearson Correlation: 0.7977542563703856 with p-value: 0.0 , Concordance Index: 0.8696652822577812\n", + "Training at Epoch 100 iteration 0 with loss 0.11071129\n", + "Validation at Epoch 100 , MSE: 0.2819463625926039 , Pearson Correlation: 0.7962812176691273 with p-value: 0.0 , Concordance Index: 0.8602355339812648\n", + "--- Go for Testing ---\n", + "Testing MSE: 0.2565965372661101 , Pearson Correlation: 0.8231646722825967 with p-value: 0.0 , Concordance Index: 0.8681803072880361\n", + "--- Training Finished ---\n" + ] + }, + { + "data": { + "image/png": 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pwMAADA+n6QceSNPgQDAz29YP+EcpHgZdb8mSahCMGB5O5Q4DMyu7ccMgIs5vYz1absOGyZWbmZVJ0VNLp7358ydXbmZWJqUJg6VLoadndFlPTyo3Myu70oRBfz8sWgQz8ieeOTNNu7/AzKxEYVCpwJVXwtataXrLljRdqXS2XmZm3aA0YbCts4nMzMquNGHgs4nMzMZXmjDw2URmZuMrTRj4bCIzs/GVJgz6+2HZMpg7N02/4AVp2mcTmZm1eaC6Tuvvh2efhVNPhVtugf3263SNzMy6Q2mODMzMbHylDQPfz8DMrKp0YeB7IJuZ1StdGJiZWb3ShoGbiczMqkoXBm4mMjOrV7owMDOzeg4DMzMrbxi4z8DMrKp0YeA+AzOzeqULAzMzq9c1YxNJWgc8CWwBno2Iha3cnpuJzMyquiYMsldHxCOt3ICbiczM6rmZyMzMuioMAvg3SSskDTRaQNKApEFJg0NDQ1PayK23pucXvxj6+qBSmWJtzcx2IN0UBq+IiMOA1wHvlXT02AUiYllELIyIhb29vZPeQKUCl102si5Yvx4GBhwIZmZdEwYR8WB+fhj4FnBEs7exZAk888zosuHhVG5mVmZdEQaSdpf0nJHXwGuAO5u9nQ0bJlduZlYW3XI20fOBbymd6jML+GpEfLfZG5kzBzZvblxuZlZmXREGEXEv8GedroeZWVl1RTNRuzQ6KgB49NH21sPMrNuUJgwqlfEvOJs/v711MTPrNqUJgyVLGg9BIcHSpe2vj5lZNylNGIx3xlAE9Pe3ty5mZt2mNGEwXlPQggXtrYeZWTcqTRgsXQo9PaPLenrcRGRmBl1yamk7jDQFLVoEW7ak17vt1rn6mJl1k9IcGYyo7UTevNljE5mZQcnCYMkS2Lp1dJnHJjIzK1kYeGwiM7PGShUGu+8+uXIzs7IoVRg89dTkys3MyqJUYdDoCuRtlZuZlUVpwsBnDJmZja80YeAzhszMxleaMFi/vtM1MDPrXqUJgxkTfNK+PjclmVl5lSYMxl5sNtb69a29GrlSSYEzY4aDx8y6T2nCoIjhYTjttOb/aFcqab3r16czl9avT9OdCASHkpk1UpowmDu32HLPPDP6R/uUU9INcMZ7HHxw+lHd1jKnnJLWO3Y7Z52VfoznzasuO29eKjvjDJg1q35dM2em57E/5LU/8vPmpcfID/5xx1XXdcopoz/fREdDjcJjokBx4HSW979NhWKanmS/cOHCGBwcLLx8pZJ+CK015s6Fz34WrrgCbrpp9DwJ3vMeuOSSztStTCqVFPDDw9Wynh5Ytsw3cbJE0oqIWDi2vDRHBv6P0FqbN6ewHRsEkI5CLr1020dPk33suuv4R0sjfxlPtI4ZMxofZXWzif7qX7JkdBBAmj7rrHbV0KatiJiWj8MPPzwmK/0s+eGHHyOPGTMiFi+OWL48YsGCCCk9H3tsxMyZaZmZM9MyIxYvHn/eeEbWP/IeSNPLl0/6v3FdXaeyjm7aTrsBgxH1v6mlaSaC9FegmdmOYio/313fTCTpeEl3S1or6bxO18fMrNs18w/crggDSTOBi4HXAQcBJ0s6qNnbWby42Ws0M+usZvV3dUUYAEcAayPi3oh4Bvg6cGKzN3LJJQ4EM9uxNGvctW4Jg72B+2umN+ayUSQNSBqUNDg0NDSlDV1ySWpnW77cN7Uxs+mvWXdq7JYwaNTyVdc1EhHLImJhRCzs7e3drg3298Pvflc9r2L5cliwYLtWaWbWdvPnN2c93RIGG4F9a6b3AR5sZwX6+2Hdus6e6DcSSFJ6Xr68c+tZvnz0Vdtz5zZeT+225s710ZZZuy1d2qQVNTrftN0PYBZwL7AfsDNwB3Dwtt4zlesMzHYkzToPvtF6xpYtXhwxd+7o6xMgle2+++T/ZNlll/qynXcePS1NvJ6dd67WpYyPqfyb0+3XGUg6AfgMMBO4PCK2mXdTuc7AzKzsxrvOYFYnKtNIRNwA3NDpepiZlVG39BmYmVkHOQzMzMxhYGZmDgMzM2Ma39xG0hCwfopvnwc80sTq7Ii8j4rxfpqY91Ex7dpPCyKi7qrdaRsG20PSYKNTq6zK+6gY76eJeR8V0+n95GYiMzNzGJiZWXnDYFmnKzANeB8V4/00Me+jYjq6n0rZZ2BmZqOV9cjAzMxqOAzMzKx8YSDpeEl3S1or6bxO16edJO0r6WZJqyX9UtJZuXyOpBslrcnPs3O5JH0u76tVkg6rWdeivPwaSYs69ZlaRdJMST+XdF2e3k/SbfnzfkPSzrl8lzy9Ns/vq1nHB3L53ZJe25lP0hqS9pR0laS78vfpKH+P6kn6H/n/2p2SviZp1679LjUa13pHfZCGx74H2J/qfRMO6nS92vj59wIOy6+fA/waOAj4BHBeLj8P+Hh+fQLwHdKd6I4Ebsvlc0j3n5gDzM6vZ3f68zV5X70f+CpwXZ7+JvDW/PoLwOL8+gzgC/n1W4Fv5NcH5e/XLqT7dNwDzOz052ri/rkSeGd+vTOwp79Hdftob+A+YLea79Cp3fpdKtuRwRHA2oi4NyKeAb4OnNjhOrVNRGyKiNvz6yeB1aQv7Imk/9zk55Py6xOBr0TyU2BPSXsBrwVujIhHI+K3wI3A8W38KC0laR/gL4Ev5WkBxwBX5UXG7qORfXcVcGxe/kTg6xHxdETcB6wlff+mPUl/BBwNXAYQEc9ExGP4e9TILGA3SbOAHmATXfpdKlsY7A3cXzO9MZeVTj4EPRS4DXh+RGyCFBjA8/Ji4+2vHX0/fgb4X8DWPD0XeCwins3TtZ/3D/siz388L78j76P9gSHgityU9iVJu+Pv0SgR8QDwSWADKQQeB1bQpd+lsoWBGpSV7txaSXsAVwNnR8QT21q0QVlso3zak/RXwMMRsaK2uMGiMcG8HXYfkf7aPQy4NCIOBZ4iNQuNp4z7iNxnciKpaecFwO7A6xos2hXfpbKFwUZg35rpfYAHO1SXjpC0EykIKhFxTS5+KB+2k58fzuXj7a8deT++AniDpHWkZsRjSEcKe+ZDfRj9ef+wL/L85wKPsmPvo43Axoi4LU9fRQoHf49GOw64LyKGIuI/gWuAl9Ol36WyhcHPgANzb/7OpE6aaztcp7bJ7Y+XAasj4qKaWdcCI2dyLAK+XVP+9nw2yJHA4/nw/3vAayTNzn/9vCaXTXsR8YGI2Cci+kjfjx9ERD9wM/DmvNjYfTSy796cl49c/tZ8hsh+wIHAv7fpY7RURPwGuF/Si3PRscCv8PdorA3AkZJ68v+9kf3Und+lTve4t/tBOrPh16Qe+SWdrk+bP/srSYeXq4CV+XECqV3yJmBNfp6Tlxdwcd5XvwAW1qzrNFJH1lrgHZ3+bC3aX6+iejbR/vk/4Frgn4FdcvmueXptnr9/zfuX5H13N/C6Tn+eJu+bQ4DB/F36F9LZQP4e1e+njwB3AXcC/0Q6I6grv0sejsLMzErXTGRmZg04DMzMzGFgZmYOAzMzw2FgZmY4DGwHJOl8SZFf75mnD5vofS2szyG5DnMazAtJ53egWmajOAxsR/Ql4Kj8ek/gw6QrZDvlkFyHujAg1fNL7a2OWb1ZEy9iNr1ExEbSJfwtka8m3SnSyLfbJdIonmYd5yMD2+GMNBPlkVnvy8VfzGUh6dSaZd8k6aeShiU9JumfJc0fs751kpZLOk3SXcAzpCGukfQRSbdLelzSI5J+kIdcGHnvqcAVeXJNTR368vy6ZiKlGzD9RNJ/5PX+S83QDyPL/FDSLZKOy9sfzjdQOQmzKXAY2I5sE/Cm/PpCUpPMUcD1AJLeQxq071eksWDeDbwU+JGk54xZ16tJN7z5CGnM/VW5fG/g06Qx6U8lDc72Y0kvy/OvBy7Ir99SU4dNjSos6fj8nt8BfwMsznW6RdLYYYsPAD4LXJQ/5ybgKkkv3OZeMWvAzUS2w4qIpyX9PE/eW9skk4fx/jhwRUScVlN+G2nsqtNJo5WOmA0cHmmQttptvLPmvTOB7wK/zO8/KyKGJN2TF1kZEWsnqPYFpDt+vS7ymPeSfpLrdA4pkEbMA46OiDV5udtJgfDfgI9NsB2zUXxkYGV1FPBHQEXSrJEHqa/hLtKdvGr9dGwQAORmmpslbQaeBf4TeBHw4rHLTiTfIOYw0u0OR25+QqS7W90K/MWYt6wZCYK83MOkI5P5mE2SjwysrEbuwvX9ceb/dsx0XbNOPl31BtKwy6fnZbaQzg7adQp1mk0a4bNRE9JvgAVjyh5tsNzTU9y2lZzDwMpqc34+ldSsM9aTY6YbDe/716SjgTdFunkJ8Ic7XD02hTr9Nm/njxvM+2OqdTZrOoeB7eiezs+7jSn/f6Qf/BdGxJVMTQ/pSOAPQSHpGFIzzX01y41Xh1Ei4ilJK4C3SDo/IrbkdS4g3SHr81Osp9mEHAa2o3uI9Bf1WyWtIt2v976I2CzpfwIXS+oFvkO6AfnepLb5H0bEVydY93eBs4EvS7qC1FfwIeCBMcv9Kj+/V9KVpH6FVeNcp/Ah0tlE10m6BNiDdAbT48CnJvG5zSbFHci2Q4uIrcA7Se3x3yfd+vT1ed4/Am8gdfb+EykQPkL6I2llgXV/D3gf6b7J15Hu2vV20p2qape7Azg/b/eWXIcXjLPO75KuYdgT+CbwBWA18MqI2JHuD2xdxnc6MzMzHxmYmZnDwMzMcBiYmRkOAzMzw2FgZmY4DMzMDIeBmZnhMDAzM+D/A1JmzTefoXRIAAAAAElFTkSuQmCC\n", + "text/plain": [ + "<Figure size 432x288 with 1 Axes>" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "model = models.model_initialize(**config)\n", + "model.train(train, val, test)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "model.save_model('./model_DeepDTA')" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.7" + } + }, + "nbformat": 4, + "nbformat_minor": 4 +}